neural-network_based-face-detection

说明：  频域的模态参数识别方法之一，可以对振动信号进行分析处理，得出结构的固有频率，阻尼比，振型系数，方法很好，程序完整，(Frequency-domain modal parameter identification methods that can analyze the vibration signal processing, draw the structure of natural frequencies, damping ratio, mode shape coefficient, very good method, program integrity,)

《滑模变结构控制matlab仿真》第六章( synovial VSC matlab simulation Chapter 6)

关于matlab软件的功能介绍,实用，方便，从基础入门，一切从零开始！！(something about Matlab)

详细介绍matlab的FFT变换的实际物理意义，并通过具体事例具体分析，简单明了，方便易懂！绝对对你明白FFT变换的意义有很大好处和实用价值。(Details of the FFT transform matlab actual physical meaning, and through a concrete analysis of concrete examples, simple and clear, easy to understand! Absolutely right you understand the meaning of FFT transform of great benefit and practical value.)

非常适合初学者的的matlab通信原理入门书，很多学校都用这个做教材！(Matlab Communication Theory Primer is ideal for beginners, many schools have done with this material!)

本资料包含kalman滤波算法的基本原理，应用场合以及仿真效果(This information includes the basic principles kalman filtering algorithms, applications, and simulation results)

This code is related to the course Digital Communications. It reproduce the error probability as a function of the SNR per bit for 16-QAM. Enjoy it!

说明：  逆合成孔径雷达成像的转台目标成像的简单程序(Inverse synthetic aperture radar imaging of a simple turntable target imaging procedures)

说明：  神经网络编码源程序，可以调用，方便使用，可进行二次开发(neural network source code can be called, for ease of use, can be re-developed.)

Finally, probability analysis, based on the chosen database, is performed and judgment whether the person is recognized is pronounced. Two different modeling techniques can be suggested for purposes of person identification or verification. The approach based on Hidden Markov Speaker Models (HMMs) with the mixtures of Gaussian distribution is text-dependent one. For this technology a speaker is described by a set of HMMs, constructing the set of speech groups spoken by that person. The speech groups may be phonemes or words [7]. The text-independent technology is rested upon Gaussian Mixture Speaker Models. For this technology each speaker is defined by only one model describing all utterances of that person. Identification in the range of both approaches is executed by evaluation of maximum a posteriori probability [7].